چکیده انگلیسی

Computerized maintenance management systems (CMMS) are common in today’s industries. CMMS can bring a large number of benefits, which include increased productivity, reduced costs, and effective utilization of the assets in any manufacturing and service producer. The list of CMMS that are available in the market has grown very rapidly during the last years. When purchasing a system, one that suits the specific needs and objectives of the company’s maintenance operations should be preferred. Several selection methods were proposed in literature. Up to now, no article has considered ambiguity and uncertainty factors when selecting effective CMMS. In addition, CMMS selection decisions involve the simultaneous consideration of multiple criteria, including tangible and intangible factors; prioritizing these factors can be a great challenge and a complex task. Therefore, no attempt has been made to incorporate fuzziness into multicriteria decision-making in the area of CMMS selection. This work proposes a fuzzy–based methodology for comparative evaluation of a number of CMMS alternatives. The proposal is based on the well-known multicriteria decision method called Analytical Hierarchy Process (AHP) with triangular numbers. An example is given to illustrate the proposed methodology. Finally, a software prototype for implementing this method was implemented. To illustrate and validate the proposed approach and the software prototype developed some details are presented and discussed.

مقدمه انگلیسی

The increase in automation and the reduction in inventories in industries have clearly put more pressure on the maintenance systems. Any disruption to production flows becomes costly and critical. This makes the maintenance function relevant to operations management to keep organizations productive and profitable along time. Therefore, computerized maintenance management systems (CMMS) are becoming increasingly important in the last few years. Using CMMS is a highly relevant issue in a production environment where the number of critical equipment is high or where the need for maintenance resources management is significant. A large variety of computer software is available on the market for maintenance management. It is not surprising that many companies have been disappointed with the results of their implemented CMMS. An extensive survey [1] reported that there is a paradox in CMMS selection and implementations. According to this survey, 62% of the respondents changed their maintenance work process to fit the CMMS characteristics and 66% customized the CMMS to fit the work process. These numbers reflect that the selection of the most suitable CMMS is a crucial task to eliminate all these problems and difficulties.
Selection and evaluation of a CMMS is a very difficult and complex task. The following five factors can be identified as the main causes of this complexity:
(1)
The tremendous number of software products available in the market.
(2)
The continual advancements and improvements in information technology (IT).
(3)
The existence of incompatibilities between various hardware and software systems.
(4)
The functional dissimilarities are difficult to evaluate among software packages.
(5)
The users lack the technical knowledge and experience for software selection decision making.
As it was previously commented, decision making in the field of maintenance management software selection has become more complex due to a large number of software products in the market, ongoing improvements in information technology, and multiple and sometimes conflicting objectives. Some methodologies and frameworks for CMMS selection and evaluation have been developed. Raouf et al. [2] presented an instrument to select suitable system using a comparative strategy and the concept of relative importance among a set of required functions in accordance to the intended use of the CMMS. More recently, Carnero and Noves [3] presented an evaluation system for the selection of computerized maintenance management software in industrial plants using multicriteria methods. Braglia et al. [4] proposed a methodology to perform a selection of the best suited CMMS within process industries. To improve the effectiveness of the methodology proposed by Braglia et al. [4], they combined AHP with a sensitivity analysis. Those evaluation systems use the AHP method in its basic version (crisp numbers). Up to now, no article has considered ambiguity and uncertainty factors when selecting effective CMMS. In addition, software selection decisions involve the simultaneous consideration of multiple criteria, including tangible and intangible factors; prioritizing these factors can be a great challenge and a complex task. Labib [5] published an investigation of the characteristics of CMMS, identified their deficiencies. In addition, Labib proposed a model to aid the decision analysis capability in CMMS under selection [5].
These factors arise as the main motivation of this research work, which is aimed at how to select an appropriate CMMS facing the strategic and operational requirements of the organization using a multicriteria decision method incorporating concepts of uncertainty and uncompleted information.
In other words, this study proposes a comprehensive CMMS selection framework in which the objective hierarchy is constructed and the appropriate attributes are specified using fuzzy numbers to provide guidance for CMSS evaluation. The analytic hierarchy process (AHP) method [6] and fuzzy numbers are applied for dealing with the ambiguities involved in the assessment of CMMS alternatives and relative importance weightings of attributes.

نتیجه گیری انگلیسی

In this paper a fuzzy-AHP-based methodology for selecting Computerized Maintenance Management Software was proposed. In order to take into account the uncertainty and in order to improve imprecision in ranking attributes and/or software alternatives, the presented approach introduces triangular numbers into traditional AHP method. Adoption of fuzzy numbers allows decisions-makers to have more freedom of estimation regarding the overall importance of attributes and real alternatives. The proposed methodology was tested on a real-world example and was found that it functions satisfactorily. We believe that this methodology is a feasible alternative to both the conventional AHP method, as well as, other fuzzy-based approaches for CMMS selection, mainly because of its simplicity and the possibility of incorporating subjective parameters and linguistic terms in expressing main software characteristics. Additionally, a fuzzy AHP based Software for selecting computerized maintenance management was proposed. The program was written in MATLAB and run on a desktop PC powered by Microsoft Windows XP. It was tested on several tests and was found to function satisfactorily. We believe that this methodology and the developed software tool is an alternative to both the conventional AHP method as well as other fuzzy-based approaches for software selection, mainly because of its simplicity and the possibility of incorporating subjective parameters.